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Data interoperability is the backbone of building reliable and efficient hyperautomated workflows. However, manipulating and formatting massive amounts of data from various sources — especially in complex JSON files — can feel overwhelming and consume significant time and resources, particularly for those still gaining technical expertise. Teams often lack or have maxed out dedicated resources to wrangle this data.
Today, we’re introducing AI Data Transformation, a powerful AI-accelerated operator that simplifies complex data transformation. It provides the testability, flexibility, and control required to manage enterprise-level workflows without writing a single line of code.
Why Data Transformation is Crucial
In hyperautomated workflows, seamless data flow between steps is crucial for optimal performance. AI Data Transformation achieves this with maximum efficiency by intelligently manipulating data as it flows to downstream steps. This powerful capability enables smooth operations by efficiently handling critical tasks such as attribute mapping, filtering, conditional statements, and aggregation functions — proactively addressing data compatibility between steps. In short, Data Transformation keeps workflows running at peak efficiency.
How AI Data Transformation Helps Security Teams
Torq’s AI translates natural language prompts into JQ commands, simplifying and democratizing JSON transformations. For those savvy in JQ, there’s full flexibility in modifying individual instructions and the generated code. Torq’s approach stands out for:
- Customizability: Edit or rewrite any command to suit your needs.
- Testability and Reproducibility: Test transformations and validate results for precise control.
- Flexibility: Easily tweak transformations without disrupting your workflow.
- Visibility: See prompts, code, and results at every step — zero guesswork.
While other solutions leave you in the dark, using monolithic parsing that makes it challenging to edit or troubleshoot, Torq keeps you in control through micro-transformations. Every transformation in Torq is testable, customizable, and modified with just a click, ensuring your automation runs precisely as intended.
Get Started
Transforming data is simple:
- Drag the transform operator into your workflow.
- Input the contextual JSON data you intend to transform, then click define transformation.
- Enter your prompt in natural language (e.g., “extract vulnerabilities”).
- Review the AI-generated JQ code and the output. Validate and edit if needed by fine-tuning with dynamic code generation or direct code editing.
- Transform your data with complete visibility and control.
- Save your work and reuse transformations as custom plans in the future.
Example Prompts
Need ideas? Here are a few natural language prompts and the associated JQ commands the Data Transformation operator could generate:
| Natural Language Prompt | AI Translated JQ Command | Security Impact |
|---|---|---|
| “Extract all high severity vulnerabilities” | .vulnerabilities[] | select(.severity == “high”) | Quickly prioritize critical security threats |
| “Group alerts by source IP” | group_by(.source_ip) | Identify potential attack patterns or compromised assets |
| “Calculate the average CVSS score” | [.[].cvss_score] | add / length | Assess the overall vulnerability landscape |
Read more about AI Data Transformation in Torq’s documentation or schedule a demo to see how it works.
